I dislike using cloud services because they may discontinue my service [1] or they may do something stupid [2] that negatively impacts me. These concerns, along with concerns about privacy [3], have led me to keep information and content I care about away from cloud services. This does make me wonder, how many people would be distraught about the loss of their content if YouTube terminated their accounts? This is not the topic today, nor is it something I can easily answer, but it is something I wonder about and would like others to consider.
Similarly, I am skeptical of “free” services. It’s incorrect to say “if something is free, you are the product” because charity does exist, but when it comes to Google, they aren’t a charity. Their current model with YouTube is to have people upload videos to their site and show ads to some users when they watch said videos. There are also paid subscriptions, but their primary monetization comes from ads. An important point is they don’t purge content on a regular basis, except in cases of ToS violations. As such, there is a (nearly) monotonically increasing function that describes the storage requirements of YouTube. This motivates my question below.
When will YouTube’s storage costs exceed their revenue if they don’t start purging old content, assuming their revenue does not increase over time?
We need the following information to answer this question:
According to Alphabet’s 2025 Q2 earnings release [4], YouTube ads made a revenue of $9.769 billion. Annualized, this is $39.076 billion, but this is only revenue, not net profit. If we assume the operating margin across Alphabet matches the operating margin of YouTube (32%), we find an approximate net profit of $12.50432 billion / year. Actual net profit could differ from this, but since we are concerned with how much data storage this could support, we don’t need to factor in how this would be taxed.
YouTube states on their official blog there are over 20 million videos uploaded per day [5]. While I don’t trust YouTube very much, and they don’t have many incentives to be honest on this topic, they seem more trustworthy in this context than the slop factory sites as they are, in fact, the ones who are hosting the content. As such, I will accept this metric.
I wrote a python script that uses a curated list of popular Google Trends searches over the past few decades [6] to search YouTube for recently uploaded videos. I ran this script and compiled a list of ~7.65 million YouTube videos.
Before continuing, I will list a few limitations of this approach:
These are the main flaws in my methodology, but any approach will be imperfect without being able to get the data directly from YouTube.
Of these 7.65 million videos, I sampled 615,222 of them and queried YouTube using yt-dlp [7] to find all video resolutions and formats YouTube will serve. It seems unlikely to me that YouTube stores each of these resolutions on their servers, but I think it is very likely that YouTube is storing the highest resolution version they are willing to serve to users.
Based on my findings, I propose a lower bound of ~396.17 MB / video, which assumes they are only storing the highest resolution version and all other versions are generated in real time via transcoding (I am confident this isn’t the case, but it provides a nice lower bound). I also propose an upper bound of ~1.44 GB / video, which assumes they are storing every resolution and format for each video they are serving.
All of the code used for this is available on my git server [8].
Using my findings above about video size and YouTube’s stated video upload rate, we find:
Lower bound:
Upper bound:
Note: These values may vary depending on rounding, but they should be similar to what anyone else would find.
GCP currently charges $26 / month for 1 TB of standard multi-region, US based, cloud storage [9]. If we assume the same 32% profit margin as before, this would cost ~$17.68 / TB / month or $212.16 / TB / year. I don’t know if this is high or low relative to what they actually pay. YouTube requires quick access to many of their videos, but many of their videos are likely retrieved infrequently. Additionally, it seems likely Alphabet’s cloud storage margins are higher than the average margins across the organization. Additionally, these are only US storage prices so this could vary depending on the regions this data is being hosted in. In any case, I think this is a fair estimate.
Given YouTube’s approximated net profit of $12.50432 billion / year and an estimated cost of $212.16 / TB / year for cloud storage, we find their profits can support an additional ~58.94 EB of data.
At the lower bound of 2.89 EB / year we find YouTube’s storage costs will surpass their current profits in ~20.39 years.
If we assume our upper bound of 10.547 EB / year we find YouTube’s storage costs will surpass their current profits in ~5.59 years.
These are very rough bounds, especially given how difficult it is to estimate the cost per TB / year for storage of this data given their retrieval needs, but we find that in ~5.59 - ~20.39 years, YouTube will be forced to start purging old content to remain profitable at their current profit rate.
[1] - https://killedbygoogle.com/
[3] - https://www.gnu.org/proprietary/proprietary-surveillance.html
[4] - https://abc.xyz/assets/cc/27/3ada14014efbadd7a58472f1f3f4/2025q2-alphabet-earnings-release.pdf
[5] - https://web.archive.org/web/20250911091711/https://blog.youtube/press/
[6] - https://www.kaggle.com/datasets/dhruvildave/google-trends-dataset
[7] - https://github.com/yt-dlp/yt-dlp
[8] - http://git.laack.co/blog/log.html
[9] - https://cloud.google.com/storage/pricing#multi-regions